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r - 如何保持具有特定值的行

问题描述

我有这样的数据

df<- structure(list(Number = structure(1:11, .Label = c("A", "AA", 
"AAA", "B", "BB", "BBB", "BBBB", "C", "CC", "CCC", "CCCC"), class = "factor"), 
    Col1 = c(31.22099237, 0, 17.16411573, 0, 0.705259568, 0, 
    2.66371587, 0, 2.720864088, 3.50268492, 0), Col2 = c(2180.612724, 
    0, 1175.574713, 0, 42.97845333, 0, 199.3804311, 0, 190.6518212, 
    247.7824952, 0), Col3 = c(3227.401883, 0, 1671.762522, 0, 
    72.9133296, 0, 344.3196473, 0, 333.6736573, 466.1626644, 
    502.3171147), Col4 = c(2735.221156, 2022.47486, 1387.524359, 
    0, 53.75158295, 0, 212.122076, 0, 191.9276388, 274.0036734, 
    0), Col5 = c(2988.544146, 2407.748537, 1627.935679, 1627.935679, 
    56.13075824, 0, 276.8770486, 0, 210.470166, 385.88476, 498.6120134
    ), Col6 = c(3371.951649, 0, 1627.659283, 0, 49.4177718, 58.1108116, 
    0, 0, 251.2365107, 431.2948353, 529.9698816), Col7 = c(0, 
    2325.388968, 1355.368616, 0, 48.20993462, 35.00690048, 0, 
    0, 219.8790867, 327.8801311, 0), Col8 = c(0, 0, 1502.048187, 
    1502.048187, 62.54871626, 338.4898404, 0, 483.841343, 261.3874571, 
    348.3883709, 0)), class = "data.frame", row.names = c(NA, 
-11L))

我想要这样的输出

output<- structure(list(Number = structure(1:4, .Label = c("A", "AA", 
"BBBB", "CCCC"), class = "factor"), Col1 = c(31.22099237, 0, 
2.66371587, 0), Col2 = c(2180.612724, 0, 199.3804311, 0), Col3 = c(3227.401883, 
0, 344.3196473, 502.3171147), Col4 = c(2735.221156, 2022.47486, 
212.122076, 0), Col5 = c(2988.544146, 2407.748537, 276.8770486, 
498.6120134), Col6 = c(3371.951649, 0, 0, 529.9698816), Col7 = c(0, 
2325.388968, 0, 0), Col8 = c(0L, 0L, 0L, 0L)), class = "data.frame", row.names = c(NA, 
-4L))

我想做以下

  1. 删除所有 NA 或零值的行
    df <- df %>% na.omit()
    df[apply(df[,-1], 1, function(x) !all(x==0)),]

  1. 删除那些在所有列中都有值的行。我想到了一个逻辑矩阵，但我想不通

  2. 保留前 5 列至少有 2 个值且后 3 列没有值或少于 2 个的行

第二个例子

df2<- structure(list(Number = structure(1:12, .Label = c("A", "AA", 
"AAA", "B", "BB", "BBB", "C", "CC", "CCC", "D", "DD", "DDD"), class = "factor"), 
    COL1 = c(406173224.8, 96923176.09, 3447270.25, 37489836.02, 
    3324543.438, 432762367.5, 667314.875, 30974699.53, 20989067.38, 
    15745820.75, 6574354.484, 11424108.27), COL2 = c(242584392.6, 
    101980486.3, 579871.7188, 0, 2308453.438, 397535765.9, 0, 
    3746376.563, 31095794.56, 0, 1030556.969, 0), COL3 = c(402236010.2, 
    115299055.9, 0, 5080776.688, 72611542.24, 728695912, 0, 0, 
    37845525.63, 1037861.25, 413324.7813, 1191412.063), COL4 = c(302854623.1, 
    267007.3438, 2396334.5, 4207015.484, 1102826.25, 117023982.5, 
    190532.1563, 1418596.625, 29904788.16, 4053600.563, 745227.2773, 
    4503530.609), COL5 = c(444770100.6, 94153154.77, 872500.375, 
    0, 0, 624809234, 0, 17644014.5, 0, 0, 495620.8125, 581600.9375
    ), COL6 = c(0, 79994610.52, 0, 0, 885095.0625, 627937144.5, 
    0, 9275362.5, 0, 0, 0, 0), COL7 = c(291344235.3, 0, 1508724.25, 
    9924209.969, 1403628.125, 103400297.8, 0, 9286129.25, 0, 
    8254331.422, 753859.4063, 3172866.969), COL8 = c(424723458.1, 
    124013613.4, 1154568.5, 11550648.31, 0, 0, 0, 0, 0, 4820875.156, 
    395120.2813, 3858119.125)), class = "data.frame", row.names = c(NA, 
-12L))

标签： r

解决方案

m = replace(df[-1], is.na(df[-1]), 0) != 0
df[(rowSums(m) != 0) &
       (rowSums(m) != NCOL(m)) &
       ((rowSums(m[,1:5]) >= 2) & rowSums(m[,(NCOL(m) - 2):NCOL(m)]) < 2),]
#   Number      Col1      Col2      Col3      Col4     Col5      Col6     Col7 Col8
#1       A 31.220992 2180.6127 3227.4019 2735.2212 2988.544 3371.9516    0.000    0
#2      AA  0.000000    0.0000    0.0000 2022.4749 2407.749    0.0000 2325.389    0
#7    BBBB  2.663716  199.3804  344.3196  212.1221  276.877    0.0000    0.000    0
#11   CCCC  0.000000    0.0000  502.3171    0.0000  498.612  529.9699    0.000    0

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